Lead / Staff AI Data Engineer
ATOSS Software SE (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted 1d ago
Reach people at ATOSS Software SE
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at ATOSS Software SE you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design and evolution of a scalable modern data platform with lakehouse architecture supporting traditional analytics and AI/GenAI workloads.
- Own migration of legacy data warehouses and lakes to modern lakehouse platforms using Databricks, Apache Spark, Delta Lake, and Kafka.
- Define and enforce architecture standards, data modeling, governance, performance, and provide technical leadership to data engineering teams.
Minimum Requirements
- Strong hands-on data engineering and platform architecture experience at Lead, Staff, or Principal level.
- Proven experience migrating legacy data platforms to modern lakehouse architectures.
- Proficient with Databricks, Apache Spark, Delta Lake, advanced Python and SQL skills.
- Experience with cloud platforms such as Azure, AWS, or GCP.
Ideal Candidate Profile
- Experienced in leading complex data platform modernization projects with architectural ownership and technical mentorship roles.
- Skilled in building production-grade batch and streaming ETL/ELT pipelines supporting AI/ML and GenAI use cases including RAG, embeddings, and vector-based retrieval.
- Comfortable making long-term architectural decisions and influencing cross-functional teams involving AI Engineers, Software Engineers, and Product teams.